What is a triangular distribution?
The triangular distribution models uncertainty when you can specify min, most likely (mode), and max values. It’s commonly used for quick estimates and PERT-like inputs.
- a: minimum (optimistic).
- c: mode / most likely value.
- b: maximum (pessimistic).
- If c is closer to a or b, the distribution becomes skewed.
PDF: for a≤x<c, 2(x-a)/((b-a)(c-a)); for c≤x≤b, 2(b-x)/((b-a)(b-c)). Mean: (a+b+c)/3. Variance: (a²+b²+c²-ab-ac-bc)/18.
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Presets
Quickly set common estimation shapes (you can tweak values after applying).
Generator
Set min/mode/max, sample size, bins, and RNG. Then generate samples and export results.
Sample stats
Samples (first 20)
FAQ
What do a, c, and b mean?
a is the minimum, c is the mode (most likely), and b is the maximum. They are often used as optimistic / most likely / pessimistic inputs.
What happens if c is not centered?
The distribution becomes skewed. If c is closer to a, it piles up more near the minimum; if c is closer to b, it piles up more near the maximum.
Is seeded RNG secure?
No. Seeded mode is for reproducibility only. Use Secure (CSPRNG) for security-sensitive randomness.
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